OpenRaiser/Intern-Atlas huggingface dataset:
A Bayesian encourages dropout
Venue: arXiv cs.LG 2014
Year: 2014

Dropout is one of the key techniques to prevent the learning from overfitting. It is explained that dropout works as a kind of modified L2 regularization. Here, we shed light on the dropout from Bayesian standpoint. Bayesian interpretation enables us to optimize the dropout rate, which is beneficial for learning of weight parameters and prediction after learning. The experiment result also encourages the optimization of the dropout.
Multi-User Flexible Coordinated Beamforming using Lattice Reduction for Massive MIMO Systems
Venue: arXiv cs.IT 2014
Year: 2014

The application of precoding algorithms in multi-user massive multiple-input multiple-output (MU-Massive-MIMO) systems is restricted by the dimensionality constraint that the number of transmit antennas has to be greater than or equal to the total number of receive antennas. In this paper, a lattice reduction (LR)-aided flexible coordinated beamforming (LR-FlexCoBF) algorithm is proposed to overcome the dimensionality constraint in overloaded MU-Massive-MIMO systems. A random user selection scheme is integrated with the proposed LR-FlexCoBF to extend its application to MU-Massive-MIMO systems with arbitary overloading levels. Simulation results show that significant improvements in terms of bit error rate (BER) and sum-rate performances can be achieved by the proposed LR-FlexCoBF precoding algorithm.
On Non-Integer Linear Degrees of Freedom of Constant Two-Cell MIMO Cellular Networks
Venue: arXiv cs.IT 2014
Year: 2014

The study of degrees of freedom (DoF) of multiuser channels has led to the development of important interference managing schemes, such as interference alignment (IA) and interference neutralization. However, while the integer DoF have been widely studied in literatures, non-integer DoF are much less addressed, especially for channels with less variety. In this paper, we study the non-integer DoF of the time-invariant multiple-input multiple-output (MIMO) interfering multiple access channel (IMAC) in the simple setting of two cells, $K$ users per cell, and $M$ antennas at all nodes. We provide the exact characterization of the maximum achievable sum DoF under the constraint of using linear interference alignment (IA) scheme with symbol extension. Our results indicate that the integer sum DoF characterization $2MK/(K+1)$ achieved by the Suh-Ho-Tse scheme can be extended to the non-integer case only when $K \leq M^2$ for the circularly-symmetric-signaling systems and $K \leq 2M^2$ for the asymmetric-complex-signaling systems. These results are further extended to the time-invariant parallel MIMO IMAC with independent subchannels.
Observations Concerning the probability of the existence of annihilators for balanced boolean functions
Venue: arXiv cs.IT 2014
Year: 2014

LFSR-based stream ciphers with nonlinear filters or combiners are susceptible to algebraic attacks using linearization methods to solve an overdefined system of nonlinear equations. And this process is greatly enhanced if the filtering or combining function has a low degree annihilator. To prevent such an attack, one would choose the parameters of that function so that the degree of its annihilator becomes large enough. As computing power is continuously increasing, a choice that seems secure today, becomes insecure tomorrow. Therefore, a tool is needed to estimate the probability of the existence of annihilators for balanced boolean functions with parameters that are beyond the current computing power. Based on experimental and calculational observations, we give in this paper an almost exact estimate of that probability, which represent a great improvement over the upper bound previously known.
Symmetry in Image Registration and Deformation Modeling
Venue: arXiv cs.CV 2014
Year: 2014

We survey the role of symmetry in diffeomorphic registration of landmarks, curves, surfaces, images and higher-order data. The infinite dimensional problem of finding correspondences between objects can for a range of concrete data types be reduced resulting in compact representations of shape and spatial structure. This reduction is possible because the available data is incomplete in encoding the full deformation model. Using reduction by symmetry, we describe the reduced models in a common theoretical framework that draws on links between the registration problem and geometric mechanics. Symmetry also arises in reduction to the Lie algebra using particle relabeling symmetry allowing the equations of motion to be written purely in terms of Eulerian velocity field. Reduction by symmetry has recently been applied for jet-matching and higher-order discrete approximations of the image matching problem. We outline these constructions and further cases where reduction by symmetry promises new approaches to registration of complex data types.
LineCAPTCHA Mobile: A User Friendly Replacement for Unfriendly Reverse Turing Tests for Mobile Devices (ICIAfS14)
Venue: arXiv cs.HC 2014
Year: 2014

As smart phones and tablets are becoming ubiquitous and taking over as the primary choice for accessing the Internet worldwide, ensuring a secure gateway to the servers serving such devices become essential. CAPTCHAs play an important role in identifying human users in internet to prevent unauthorized bot attacks. Even though there are numerous CAPTCHA alternatives available today, there are certain drawbacks attached with each alternative, making them harder to find a general solution for the necessity of a CAPTCHA mechanism. With the advancing technology and expertise in areas such as AI, cryptography and image processing, it has come to a stage where the chase between making and breaking CAPTCHAs are even now. This has led the humans with a hard time deciphering the CAPTCHA mechanisms. In this paper, we adapt a novel CAPTCHA mechanism named as LineCAPTCHA to mobile devices. LineCAPTCHA is a new reverse Turing test based on drawing on top of Bezier curves within noisy backgrounds. The major objective of this paper is to report the implementation and evaluation of LineCAPTCHA on a mobile platform. At the same time we impose certain security standards and security aspects for establishing LineCAPTCHAs which are obtained through extensive measures. Independency from factors such as the fluency in English language, age and easily understandable nature of it inclines the usability of LineCAPTCHA. We believe that such independency will favour the main target of LineCAPTCHA, user friendliness and usability.
Locating Tables in Scanned Documents for Reconstructing and Republishing (ICIAfS14)
Venue: arXiv cs.CV 2014
Year: 2014

Pool of knowledge available to the mankind depends on the source of learning resources, which can vary from ancient printed documents to present electronic material. The rapid conversion of material available in traditional libraries to digital form needs a significant amount of work if we are to maintain the format and the look of the electronic documents as same as their printed counterparts. Most of the printed documents contain not only characters and its formatting but also some associated non text objects such as tables, charts and graphical objects. It is challenging to detect them and to concentrate on the format preservation of the contents while reproducing them. To address this issue, we propose an algorithm using local thresholds for word space and line height to locate and extract all categories of tables from scanned document images. From the experiments performed on 298 documents, we conclude that our algorithm has an overall accuracy of about 75% in detecting tables from the scanned document images. Since the algorithm does not completely depend on rule lines, it can detect all categories of tables in a range of scanned documents with different font types, styles and sizes to extract their formatting features. Moreover, the algorithm can be applied to locate tables in multi column layouts with small modification in layout analysis. Treating tables with their existing formatting features will tremendously help the reproducing of printed documents for reprinting and updating purposes.
On recoverability properties of fixed measurement matrices
Venue: arXiv cs.IT 2014
Year: 2014

The purpose of this paper is to extend a result by Donoho and Huo, Elad and Bruckstein, Gribnoval and Nielsen on sparse representations of signals in dictionaries to general matrices. We consider a general fixed measurement matrix, not necessarily a dictionary, and derive sufficient condition for having unique sparse representation of signals in this matrix. Currently, to the best of our knowledge, no such method exists. In particular, if matrix is a dictionary, our method is at least as good as the method proposed by Gribnoval and Nielsen.
Coordinate Tomlinson-Harashima Precoding Design for Overloaded Multi-user MIMO Systems
Venue: arXiv cs.IT 2014
Year: 2014

Tomlinson-Harashima precoding (THP) is a nonlinear processing technique employed at the transmit side to implement the concept of dirty paper coding (DPC). The perform of THP, however, is restricted by the dimensionality constraint that the number of transmit antennas has to be greater or equal to the total number of receive antennas. In this paper, we propose an iterative coordinate THP algorithm for the scenarios in which the total number of receive antennas is larger than the number of transmit antennas. The proposed algorithm is implemented on two types of THP structures, the decentralized THP (dTHP) with diagonal weighted filters at the receivers of the users, and the centralized THP (cTHP) with diagonal weighted filter at the transmitter. Simulation results show that a much better bit error rate (BER) and sum-rate performances can be achieved by the proposed iterative coordinate THP compared to the previous linear art.
Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14)
Venue: arXiv cs.IR 2014
Year: 2014

Plagiarism is known as illegal use of others' part of work or whole work as one's own in any field such as art, poetry, literature, cinema, research and other creative forms of study. Plagiarism is one of the important issues in academic and research fields and giving more concern in academic systems. The situation is even worse with the availability of ample resources on the web. This paper focuses on an effective plagiarism detection tool on identifying suitable intra-corpal plagiarism detection for text based assignments by comparing unigram, bigram, trigram of vector space model with cosine similarity measure. Manually evaluated, labelled dataset was tested using unigram, bigram and trigram vector. Even though trigram vector consumes comparatively more time, it shows better results with the labelled data. In addition, the selected trigram vector space model with cosine similarity measure is compared with tri-gram sequence matching technique with Jaccard measure. In the results, cosine similarity score shows slightly higher values than the other. Because, it focuses on giving more weight for terms that do not frequently exist in the dataset and cosine similarity measure using trigram technique is more preferable than the other. Therefore, we present our new tool and it could be used as an effective tool to evaluate text based electronic assignments and minimize the plagiarism among students.
Value Function in Maximum Hands-off Control
Venue: arXiv cs.SY 2014
Year: 2014

In this brief paper, we study the value function in maximum hands-off control. Maximum hands-off control, also known as sparse control, is the L0-optimal control among the admissible controls. Although the L0 measure is discontinuous and non- convex, we prove that the value function, or the minimum L0 norm of the control, is a continuous and strictly convex function of the initial state in the reachable set, under an assumption on the controlled plant model. This property is important, in particular, for discussing the sensitivity of the optimality against uncertainties in the initial state, and also for investigating the stability by using the value function as a Lyapunov function in model predictive control.
Texture analysis using volume-radius fractal dimension
Venue: arXiv cs.CV 2014
Year: 2014

Texture plays an important role in computer vision. It is one of the most important visual attributes used in image analysis, once it provides information about pixel organization at different regions of the image. This paper presents a novel approach for texture characterization, based on complexity analysis. The proposed approach expands the idea of the Mass-radius fractal dimension, a method originally developed for shape analysis, to a set of coordinates in 3D-space that represents the texture under analysis in a signature able to characterize efficiently different texture classes in terms of complexity. An experiment using images from the Brodatz album illustrates the method performance.
Sparkle Vision: Seeing the World through Random Specular Microfacets
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, we study the problem of reproducing the world lighting from a single image of an object covered with random specular microfacets on the surface. We show that such reflectors can be interpreted as a randomized mapping from the lighting to the image. Such specular objects have very different optical properties from both diffuse surfaces and smooth specular objects like metals, so we design special imaging system to robustly and effectively photograph them. We present simple yet reliable algorithms to calibrate the proposed system and do the inference. We conduct experiments to verify the correctness of our model assumptions and prove the effectiveness of our pipeline.
Accurate Distributed Time Synchronization in Mobile Wireless Sensor Networks from Noisy Difference Measurements
Venue: arXiv cs.SY 2014
Year: 2014

We propose a distributed algorithm for time synchronization in mobile wireless sensor networks. Each node can employ the algorithm to estimate the global time based on its local clock time. The problem of time synchronization is formulated as nodes estimating their skews and offsets from noisy difference measurements of offsets and logarithm of skews; the measurements acquired by time-stamped message exchanges between neighbors. A distributed stochastic approximation based algorithm is proposed to ensure that the estimation error is mean square convergent (variance converging to 0) under certain conditions. A sequence of scheduled update instants is used to meet the requirement of decreasing time-varying gains that need to be synchronized across nodes with unsynchronized clocks. Moreover, a modification on the algorithm is also presented to improve the initial convergence speed. Simulations indicate that highly accurate global time estimates can be achieved with the proposed algorithm for long time durations, while the errors in competing algorithms increase over time.
Predicting User Engagement in Twitter with Collaborative Ranking
Venue: arXiv cs.IR 2014
Year: 2014

Collaborative Filtering (CF) is a core component of popular web-based services such as Amazon, YouTube, Netflix, and Twitter. Most applications use CF to recommend a small set of items to the user. For instance, YouTube presents to a user a list of top-n videos she would likely watch next based on her rating and viewing history. Current methods of CF evaluation have been focused on assessing the quality of a predicted rating or the ranking performance for top-n recommended items. However, restricting the recommender system evaluation to these two aspects is rather limiting and neglects other dimensions that could better characterize a well-perceived recommendation. In this paper, instead of optimizing rating or top-n recommendation, we focus on the task of predicting which items generate the highest user engagement. In particular, we use Twitter as our testbed and cast the problem as a Collaborative Ranking task where the rich features extracted from the metadata of the tweets help to complement the transaction information limited to user ids, item ids, ratings and timestamps. We learn a scoring function that directly optimizes the user engagement in terms of nDCG@10 on the predicted ranking. Experiments conducted on an extended version of the MovieTweetings dataset, released as part of the RecSys Challenge 2014, show the effectiveness of our approach.
Minimizing the Latency of Quantum Circuits during Mapping to the Ion-Trap Circuit Fabric
Venue: arXiv cs.ET 2014
Year: 2014

Quantum computers are exponentially faster than their classical counterparts in terms of solving some specific, but important problems. The biggest challenge in realizing a quantum computing system is the environmental noise. One way to decrease the effect of noise (and hence, reduce the overhead of building fault tolerant quantum circuits) is to reduce the latency of the quantum circuit that runs on a quantum circuit. In this paper, a novel algorithm is presented for scheduling, placement, and routing of a quantum algorithm, which is to be realized on a target quantum circuit fabric technology. This algorithm, and the accompanying software tool, advances state-of-the-art in quantum CAD methodologies and methods while considering key characteristics and constraints of the ion-trap quantum circuit fabric. Experimental results show that the presented tool improves results of the previous tool by about 41%.
Combining Conventional Cryptography with Information Theoretic Security
Venue: arXiv cs.IT 2014
Year: 2014

This paper highlights security issues that can arise when incorrect assumptions are made on the capabilities of an eavesdropper. In particular, we analyze a channel model based on a split Binary Symmetric Channel (BSC). Corresponding security parameters are chosen based on this channel model, and assumptions on the eavesdroppers capabilities. A gradual relaxation of the restrictions on the eavesdropper's capabilities will be made, and the resulting loss of security will be quantified. An alternative will then be presented that is based on stochastic encoding and creating artificially noisy channels through the usage of private keys. The artificial channel will be constructed through a deterministic process that will be computationally intractable to reverse.
Priority based bandwidth allocation in wireless sensor networks
Venue: arXiv cs.NI 2014
Year: 2014

Most of the sensor network applications need real time communication and the need for deadline aware real time communication is becoming eminent in these applications. These applications have different dead line requirements also. The real time applications of wireless sensor networks are bandwidth sensitive and need higher share of bandwidth for higher priority data to meet the dead line requirements. In this paper we focus on the MAC layer modifications to meet the real time requirements of different priority data. Bandwidth partitioning among different priority transmissions is implemented through MAC layer modifications. The MAC layer implements a queuing model that supports lower transfer rate for lower priority packets and higher transfer rate for real time packets with higher priority, minimizing the end to end delay. The performance of the algorithm is evaluated with varying node distribution.
Improving Persian Document Classification Using Semantic Relations between Words
Venue: arXiv cs.IR 2014
Year: 2014

With the increase of information, document classification as one of the methods of text mining, plays vital role in many management and organizing information. Document classification is the process of assigning a document to one or more predefined category labels. Document classification includes different parts such as text processing, term selection, term weighting and final classification. The accuracy of document classification is very important. Thus improvement in each part of classification should lead to better results and higher precision. Term weighting has a great impact on the accuracy of the classification. Most of the existing weighting methods exploit the statistical information of terms in documents and do not consider semantic relations between words. In this paper, an automated document classification system is presented that uses a novel term weighting method based on semantic relations between terms. To evaluate the proposed method, three standard Persian corpuses are used. Experiment results show 2 to 4 percent improvement in classification accuracy compared with the best previous designed system for Persian documents.
Disjunctive Normal Networks
Venue: arXiv cs.LG 2014
Year: 2014

Artificial neural networks are powerful pattern classifiers; however, they have been surpassed in accuracy by methods such as support vector machines and random forests that are also easier to use and faster to train. Backpropagation, which is used to train artificial neural networks, suffers from the herd effect problem which leads to long training times and limit classification accuracy. We use the disjunctive normal form and approximate the boolean conjunction operations with products to construct a novel network architecture. The proposed model can be trained by minimizing an error function and it allows an effective and intuitive initialization which solves the herd-effect problem associated with backpropagation. This leads to state-of-the art classification accuracy and fast training times. In addition, our model can be jointly optimized with convolutional features in an unified structure leading to state-of-the-art results on computer vision problems with fast convergence rates. A GPU implementation of LDNN with optional convolutional features is also available
Fast and Scalable Inference of Multi-Sample Cancer Lineages
Venue: arXiv cs.CE 2014
Year: 2014

Somatic variants can be used as lineage markers for the phylogenetic reconstruction of cancer evolution. Since somatic phylogenetics is complicated by sample heterogeneity, novel specialized tree-building methods are required for cancer phylogeny reconstruction. We present LICHeE (Lineage Inference for Cancer Heterogeneity and Evolution), a novel method that automates the phylogenetic inference of cancer progression from multiple somatic samples. LICHeE uses variant allele frequencies of SSNVs obtained by deep sequencing to reconstruct multi-sample cell lineage trees and infer the subclonal composition of the samples. LICHeE is open-sourced and available at http://viq854.github.io/lichee.
Maze Solving Automatons for Self-Healing of Open Interconnects: Modular Add-on for Circuit Boards
Venue: arXiv cs.ET 2014
Year: 2014

We present the circuit board integration of a self-healing mechanism to repair open faults. The electric field driven mechanism physically restores fractured interconnects in electronic circuits and has the ability to solve mazes. The repair is performed by conductive particles dispersed in an insulating fluid. We demonstrate the integration of the healing module onto printed circuit boards and the ability of maze solving. We model and perform experiments on the influence of the geometry of the conductive particles as well as the terminal impedances of the route on the healing efficiency. The typical heal rate is 10 $μ$m/s with healed route having resistance of 100 $Ω$ to 20 k$Ω$ depending on the materials and concentrations used.